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8/2/2019 Client Aware Algorithm for Web Cluster
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A Client-Aware Dispatching Algorithm for Web ClustersProviding Multiple Services
Emiliano CasalicchioDept. of Computer EngineeringUniversity of Roma Tor Vergata
Roma, Italy, 00133
Michele ColajanniDept. of Information Engineering
University of ModenaModena, Italy, 41100
ABSTRACT
Categories and Subject Descriptors
General Terms
Keywords
Copyright is held by the author/owner.WWW10, May 1-5, 2001, Hong Kong.Copyright 2001 ACM 1-58113-348-0/01/0005 ... 5.00.
1. INTRODUCTION
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2. WEB CLUSTERS
2.1 Architecture
NetworkAreaLocal
Client Requests
WideAreaNetwork
0 0 0 00 0 0 00 0 0 00 0 0 00 0 0 01 1 1 11 1 1 11 1 1 11 1 1 11 1 1 10 0 0 00 0 0 01 1 1 11 1 1 10 0 00 0 01 1 11 1 1 0 0 0 00 0 0 00 0 0 00 0 0 00 0 0 01 1 1 11 1 1 11 1 1 11 1 1 11 1 1 10 0 0 00 0 0 01 1 1 11 1 1 10 0 00 0 01 1 11 1 10 0 0 00 0 0 00 0 0 00 0 0 00 0 0 01 1 1 11 1 1 11 1 1 11 1 1 11 1 1 10 0 0 00 0 0 01 1 1 11 1 1 10 0 00 0 01 1 11 1 1000000000000111111111111 000000000000111111111111 000000000000111111111111 000000000000111111111111000000000000111111111111 000000000000111111111111Backend 1 Backend MBackend 2
Web server 2 Web server 3 Web server NWeb server 1
Web switch
2.2 Web switches
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-
3. WEB SWITCH ALGORITHMS
3.1 Static and dynamic global scheduling
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3.2 Client-aware policy
4. SIMULATION EXPERIMENTS
4.1 System model
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Web switch
denotes the next server in the assignment for each class of Web service*
N DB CB DCB N DB CB DCB
RR Final state
CAP Final state
Initial state* ***
1 0 01
N DB CB DCB
0 0 1 1
N DB CB DCB
3 1 10 2 3 1
N DB CB DCB N DB CB DCB
2 11 2 11 1
2 2 1 01 1 2 2
N DB CB DCB N DB CB DCB
2
0LARD Final state( DB, CB > AN, DCB > B )
CAP
RR
LARD
Algorithm Web server A
N_1, CB_2, DCB_1, DB_2
N_1, CB_2, DB_1
CB_1, CB_2, DB_1, DB_2
Web server B
CB_1, DCB_1, N_2, DB_2
CB_1, DB_1, N_2
N_1, DCB_1, N_2
Web server A Web server B
DB_2, N_2, DCB_1, DB_1, CB_2, CB_1, N_1
Sequence Assignement
4.2 Workload model
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4.3 Simulation results
4.3.1 Optimal tuning of server-aware policies
-
4.3.2 Web publishing
4.3.3 Web transaction
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0
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20
30
40
50
60
70
80
10 40 70 100
90-percentileofPageresponcetime(sec.)
Tgat (sec.)
WRR_numWRR_time
RRRAN
0
10
20
30
40
50
60
70
80
10 40 70 100
90-percentileofPageresponcetime(sec.)
Tgat (sec.)
WRR_numWRR_time
RRRAN
4.3.4 Web commerce
0
0.2
0.4
0.6
0.8
1
0 2 4 6 8 10
CumulativeFrequency
Page Latency Time (sec.)
CAPLARDWRR
0
0.2
0.4
0.6
0.8
1
0 2 4 6 8 10
CumulativeFrequency
Page Latency Time (sec.)
CAPLARDWRR
0
0.2
0.4
0.6
0.8
1
0 5 10 15 20 25 30
CumulativeFrequency
Page Latency Time (sec.)
CAPLARDWRR
StaticPartitioning
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5. PROTOTYPE EXPERIMENTS
5.1 Prototype architecture
0
0.2
0.4
0.6
0.8
1
0 5 10 15 20 25 30
CumulativeFrequency
Page Latency Time (sec.)
CAPLARDWRR
StaticPartitioning
0
0.2
0.4
0.6
0.8
1
0 5 10 15 20 25 30
CumulativeFrequency
Page Latency Time (sec.)
CAPLARDWRR
StaticPartitioning
0
0.2
0.4
0.6
0.8
1
0 5 10 15 20 25 30
CumulativeFrequency
Page Latency Time (sec.)
CAPLARDWRR
StaticPartitioning
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5.2 Experimental results
50
60
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90
100
110
160 200 240 280
Throughput[conn/sec]
Active clients
CAPLARD
50
60
70
80
90
100
110
120
160 200 240 280
Throughput[conn/sec]
Active clients
CAP
LARD
50
60
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80
90
100
110
120
160 200 240 280
Throughput[conn/sec]
Active clients
CAPLARD
6. CONCLUSIONS
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0
0.2
0.4
0.6
0.8
1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
cumulativefrequency
CPU Utilization
CAP (Min)LARD (Min)
CAP (Max)LARD (Max)
Acknowledgments
7. REFERENCES
544